Update: We now are an official association!
I recently attended the first Workshop for Research Software Engineers at Oxford University. Organized by the SSI, I was on the steering committee and this event came out of our position paper last year. Hot on the heels of a recent article in the Times Higher Education, the aim of the workshop was to bring those people together who work in research labs but actually spend most of their time writing software.
Topics of discussion focused around the importance of software in research, software development workflows, quality control, notable tools, getting recognition for software (a real problem in academia), the role of funding bodies, and career progression. Continue reading
If you think there is more to the world than “functional cloud based self learning big data analytic enterprise visualization dashboards” please read on.
Those that follow me on twitter will have noticed I have recently taken over the organization of the London Big-O Algorithms meetup. Originally founded by Zack almost (almost a year ago) it fell quiet after the first meetup as things came up and Zack eventually moved to better weather in California. I was a strong supporter of the project from the beginning and when meetup.com sent all members an email saying the group was in danger of deletion I decided to put my money where my mouth was and took over organization.
The aim of the group is to focus on the fundamental algorithms & datastructures that developers rely on every day to make things efficient, fast, and scalable. These are things that will come up in every decent job interview and its easy to forget them in day to day work or the buzzword of the week. Any application goes, be it computational fluid dynamics or high frequency trading. Just as long as the focus is on the underlying algorithms & datastructures and it is delivered in an engaging, accessible way.
Skillsmatter have been kind enough to host us and Im happy to announce we have 2 great speakers lined up for our first meetup titled Lockless Tables, NegaMax, and Numerical Optimization in Machine Learning.